received by the International Bureau on 25 December 2017 (25.12.2017)

Please substitute the following claims for the same numbered claims in the application.

I/We claim:

1. A sleep monitoring and tracking system (100) comprising:

a sensing device (102) that measures a plurality of vibration data of an occupant, wherein the plurality of vibration data of the occupant comprises (i) heart beat data, (ii) inhalation and exhalation data, (iii) body movement data, and (iv) muscle twitch data, wherein the sensing device (102) comprises:

a set of sensor units (110) that capture the plurality of vibration data of the occupant, wherein the set of sensor units (110) extract (i) heart rates from the heart beat data (ii) breathing rates from the inhalation and exhalation data, (iii) body movement signal from the body movement data and (iv) muscle twitch signal from the muscle twitch data to obtain a plurality of extracted vibration data of the occupant, wherein the set of sensor units (110) are placed below a mattress or above a bed; and

a transmitter unit (112) that transmits the plurality of extracted vibration data of the occupant;

a server (106) that receives the plurality of extracted vibration data of the occupant te from the sensing device (102) via a communication network, wherein the server (106) comprises:

a communication module (126) comprises a receiver module and a transmitter module,

15 wherein the receiver module receives the plurality of extracted vibration data from the transmitter unit (112) of the sensing device (102) via the communication network; a database (128) that stores the plurality of extracted vibration data from the set of sensor units (110); and

a processor (124) that processes the plurality of extracted vibration data of the occupant and determines a sleep stage of the occupant by employing a machine learning algorithm which receives the plurality of extracted vibration data of the occupant as input; and

an alarm that makes an alert to the occupant when the occupant completes a pre- determined number of sleep cycles, wherein each sleep cycle comprises a plurality of sleep stages. 2. The system of claim 1, wherein the plurality of vibration data of the occupant comprises snoring data, wherein the set of sensor units (110) extract the snoring signals from the snoring data, wherein the set of sensor units (110) capture room temperature data, humidity data, light data, air quality data and noise level data around the occupant. 3. The system of claim 1 , wherein the plurality of sleep stages comprises (i) Non-Rapid Eye Movement (NREM), (ii) Rapid Eye Movement (REM), wherein the NREM comprises (i) NREM 1 , (ii) NREM 2 and (iii) NREM 3.

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4. The system of claim 1, wherein the sensing device (102) comprises multiple sets of sensor units (110) for capturing the plurality of vibration data for each occupant. 5. The system of claim 4, wherein each set of sensor units (110) comprises an array of Piezoelectric Vinylidene Fluoride (PV DF) sensors. 6. The system of claim 1, wherein the the server (106) (i) detects a plurality of sleep irregularities of the occupant, and sends a notification to a designated recipient, wherein the notification comprises a suggestion for the sleep irregularities, wherein the suggestion chosen from the database (128) that lists the sleep irregularities mapped against the suggestion. 7. The system of claim 1, wherein the server (106) classification hypothesis and neural network (125) is trained on the extracted features using chronological plurality of vibration data from polysomnography. 8. The system of claim 1, wherein the set of sensor units (110) check if the occupant is on the mattress. 9. A method for sleep monitoring and tracking, the method comprising:

17 measuring a plurality of vibration data of an occupant, wherein the plurality of vibration data of the occupant comprises (i) heart beat data, (ii) inhalation and exhalation data, (iii) body movement data and (iv) muscle twitch data;

capturing the plurality of vibration data of the occupant;

extracting (i) heart rates from the heart beat data (ii) breathing rates from the inhalation and exhalation data, (iii) body movement signal from the body movement data and (iv) muscle twitch signal from the muscle twitch data to obtain a plurality of extracted vibration data of the occupant;

transmitting the plurality of extracted vibration data of the occupant from a sensing device (102) to a server (106) via a communication network;

receiving the plurality of extracted vibration data of the occupant to from the sensing device (102) by the server (106);

dividing the plurality of extracted vibration data of the occupant corresponding to the occupant into a plurality of sub intervals;

determining a sleep stage of the occupant by employing a machine learning algorithm which receives the plurality of extracted vibration data of the occupant as input;

alerting the occupant when the occupant completes a pre -determined number of cycles, wherein each sleep cycle comprises a plurality of sleep stages. 10. The method of claim 9, wherein the method comprises the step of checking if the occupant is on the mattress.

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11. The method of claim 9, wherein the method comprises the step of measuring the plurality of sensor units (110) in a sensing device (102) that are active.

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